research
∙
03/10/2020
Error Estimation for Sketched SVD via the Bootstrap
In order to compute fast approximations to the singular value decomposit...
share
research
∙
03/04/2020
Forecasting Sequential Data using Consistent Koopman Autoencoders
Recurrent neural networks are widely used on time series data, yet such ...
research
∙
09/13/2019
Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching
Although the operator (spectral) norm is one of the most widely used met...
research
∙
09/02/2019
Randomized methods to characterize large-scale vortical flow network
We demonstrate the effective use of randomized methods for linear algebr...
research
∙
05/26/2019
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction
In addition to providing high-profile successes in computer vision and n...
research
∙
04/07/2019
JumpReLU: A Retrofit Defense Strategy for Adversarial Attacks
It has been demonstrated that very simple attacks can fool highly-sophis...
research
∙
02/20/2019
Shallow Learning for Fluid Flow Reconstruction with Limited Sensors and Limited Data
In many applications, it is important to reconstruct a fluid flow field,...
research
∙
11/28/2018
RetinaMatch: Efficient Template Matching of Retina Images for Teleophthalmology
Retinal template matching and registration is an important challenge in ...
research
∙
04/01/2018
Sparse Principal Component Analysis via Variable Projection
Sparse principal component analysis (SPCA) has emerged as a powerful tec...
research
∙
02/23/2018
Diffusion Maps meet Nyström
Diffusion maps are an emerging data-driven technique for non-linear dime...
research
∙
11/06/2017
Randomized Nonnegative Matrix Factorization
Nonnegative matrix factorization (NMF) is a powerful tool for data minin...
research
∙
03/27/2017
Randomized CP Tensor Decomposition
The CANDECOMP/PARAFAC (CP) tensor decomposition is a popular dimensional...
research
∙
02/07/2017
Randomized Dynamic Mode Decomposition
This paper presents a randomized algorithm for computing the near-optima...
research
∙
08/06/2016
Randomized Matrix Decompositions using R
Matrix decompositions are fundamental tools in the area of applied mathe...
research
∙
12/14/2015
Compressed Dynamic Mode Decomposition for Background Modeling
We introduce the method of compressed dynamic mode decomposition (cDMD) ...
research
∙
12/11/2015